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Machine Learning Algorithm Detects Cervical Cancer

Jan 24, 2019 | News and Media Coverage

HOSPIMEDICA (January 24, 2019)

A novel colposcope uses an automated visual evaluation (AVE) algorithm to detect cervical cancer from even a single image.

The MobileODT  Enhanced Visual Assessment (EVA) system is a compact colposcope designed for durability and portability. Features include an ultra-bright powered light source with cross-polarization (to reduce glare); a complementary metal-oxide semiconductor (CMOS) sensor with 13 megapixel resolution; and a powerful 4X optical/16X digital zoom magnification lens that provides a working distance of 225-400 mm. The rechargeable, long-lasting battery provides up to 10 hours of continuous use.

Secure software allows for real-time visualization of the cervix, with enhancement filters that can be applied directly to captured images. Secure online data management allows users to document cases, add annotations, and export the information to an electronic medical record (EMR), simplifying the medical workflow. In addition, a cloud-based information system (EVA Cloud) provides secure access to real time data so as to monitor provider utilization, identify cases reviewed, collect anonymized patient statistics, and enhance quality control and quality improvement opportunities.

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